Towards Detecting Suspicious Features in IoT Botnet
Quoc-Dung Ngo · 2023
Botnet often hides malicious behavior and reveals malicious behavior only when triggering conditions are met. Behaviors with trigger conditions make it difficult to analyze and detect, which requires manual analysis and is time-consuming. Meanwhile, with the strong development of technology and distributed characteristics of IoT devices, the number of botnets is increasing, and the focus is on IoT devices but the ability to manually analyze IoT botnet malware is still limited. Therefore, in this paper, we proposed a semi-automatic analysis solution to detect the conditions that trigger the malicious behavior of IoT botnets. The experimental results on the actual IoT botnet sample set initially achieved positive results, creating a premise for future in-depth research on the characteristics of IoT botnet.